AMELIE is a precision medicine technology that provides care givers with personalized and continuous patient diagnosis support.
AMELIE utilizes Natural Language Processing of medical knowledgebase of patient's medical record, combined with Machine Learning based analysis of WGS/WES genomic data, to provide continuous personalized diagnosis.
AMELIE was developed based on research conducted in the Bejerano Lab at Stanford University's school of Medicine and the Computer Science Department.
I worked closely with the Stanford Bioinformatics Professor who led the science behind AMELIE, and with the business founders, to productize the Stanford based research. I've led the frontend design and development, including recruit of development team, definition of product stories, management of QA process till final launch. I've defined with the founding team the roadmap for the first design partners pilots, aiming to assess the academic based research in a clinical environment. First pilot is aimed in 3rd quarter of 2020.